Method for optimum economy cruise speed in an aircraft

ABSTRACT

Method for calculating an optimum economy cruise speed in an aircraft and its use is disclosed herein. The method includes receiving a plurality of flight parameters including a weight of the aircraft, an aircraft bearing and an atmospheric pressure and temperature, a wind speed and a wind bearing at the altitude of the aircraft; calculating a cost index associated with the flight of the aircraft; calculating a weight coefficient of the aircraft, a cost index coefficient, a wind Mach number and an absolute value of a difference between the wind bearing and the aircraft bearing. Additionally, the method includes calculating an optimum Mach number of the aircraft, which provides the optimum economy cruise speed. The calculation of the optimum Mach number includes the weight coefficient, the cost index coefficient, the wind Mach number and the absolute value of the difference between the wind bearing and aircraft bearing.

FIELD

The present disclosure relates to a method for calculating an optimum economy cruise (ECON) speed in an aircraft, and more specifically, optimizing the cruise speed of an aircraft to minimize flight costs for given conditions.

BACKGROUND

Minimizing the flight costs for given atmospheric conditions, cost index and flight distances may include obtaining the optimum Mach number for a given altitude. Generally the given altitude is provided by an Air Traffic Control (ATC) entity. Present solutions for optimizing aircraft flight costs are mainly focused on aircraft preliminary design instead of actual flight management system (FMS) implementation or trajectory prediction. These solutions contain significant simplifications such as ignoring factors (e.g., wind, parabolic drag polar, and constant thrust specific fuel consumption (TSFC)), that make the results inappropriate for the operational use thereof. Even if wind is considered, conventional solutions apply wind as a correction after obtaining an optimum Mach number for a zero wind condition.

SUMMARY

The subject matter of the present application has been developed in response to the present state of the art, and in particular, in response to the shortcomings of conventional solutions for optimizing the economy cruise speed of an aircraft, which have not yet been fully solved by currently available techniques. Accordingly, the subject matter of the present application has been developed to provide apparatuses, systems, and methods for optimizing the economy cruise speed of an aircraft, that overcome at least some of the above-discussed shortcomings of prior art techniques.

According to some embodiments, disclosed herein is a method, system, and computer program product for calculating an optimum economy cruise speed in an aircraft and the use thereof, and a method for controlling an aircraft to fly at the optimum economy cruise speed. The method of the present disclosure provides a significant improvement over existing solutions as it takes into account the influence of the crosswind for calculating the optimum Mach number (that will provide the minimum costs), in addition to also considering a realistic drag polar that includes the compressibility effects and fuel consumption dependencies with speed and thrust. Another advantage of the present disclosure is a method for controlling an aircraft to fly at an optimum economy cruise speed as calculated above.

In one embodiment, a method for calculating an optimum economy cruise speed for an aircraft is disclosed. This method includes receiving a plurality of flight parameters including at least a weight of the aircraft, an aircraft bearing, an atmospheric pressure, an atmospheric temperature, a wind speed, and a wind bearing at a flight altitude of the aircraft. The method also includes calculating a cost index coefficient associated with the flight of the aircraft is calculated. The cost index coefficient is based on at least a cost index, the atmospheric pressure, and the atmospheric temperature. A weight coefficient of the aircraft is also calculated based on at least the weight of the aircraft and the atmospheric pressure at the altitude of the aircraft. Also calculated are a wind Mach number and an absolute value of a difference between the wind bearing and the aircraft bearing. An optimum Mach number of the aircraft is calculated, which provides the optimum economy cruise speed, wherein the calculation further comprises the weight coefficient, the cost index coefficient, the wind Mach number, and the absolute value of the difference between the wind bearing and the aircraft bearing. The Mach number (e.g., aircraft Mach number or wind Mach number) of the aircraft/wind may be the division of the speed (of the aircraft or wind respectively) by the speed of sound, where the speed of sound is a function of the atmospheric temperature.

In some implementations, the cost index coefficient may be a dimensionless parameter calculated from a given cost index (CI), ambient pressure, and ambient temperature. The cost index may be fixed for each flight. However, the cost index coefficient can continuously change along a flight path of the aircraft. The cost index coefficient may be specifically calculated as the ratio of the cost index divided by the product of the atmospheric pressure and the square root of the atmospheric temperature. In turn, the cost index may relate a fuel cost of the aircraft and an hourly cost of the aircraft. For example, the cost index may be calculated as a coefficient relating the ratio between the hourly costs of the aircraft (e.g., aircraft amortization, salaries, connection losses, etc.) and the fuel costs of the aircraft (e.g., kilogram per second units). The cost index is often employed by the airlines to optimize the aircraft's flight. Moreover, the cost index is an input parameter that can vary depending on each flight.

In some implementations of the method, the fuel load of the aircraft may be dynamically and continuously measured in order to calculate the weight of the aircraft. The weight of the aircraft depends directly on the current fuel load, so there is a direct link between the remaining fuel load and the calculated optimum speed. Even if it were to be assumed that the wind conditions and the direction of the aircraft had not changed during flight, the aircraft weight reduction, due to the fuel consumption, would change the weight coefficient and then the optimum speed of the aircraft.

According to some implementations of the method, the atmospheric pressure at the altitude of the aircraft may also be dynamically and continuously measured in order to calculate the altitude of the aircraft. The present atmospheric pressure at a point in time along a flight path of the aircraft will depend on the altitude of the aircraft. Note that when the altitude of the aircraft is mentioned, it is referring to the pressure altitude instead of the geometric altitude.

In yet some implementations of the method, the calculation of the optimum Mach number may further include considering a realistic drag polar that includes compressibility effects and fuel consumption dependencies with aircraft speed and aircraft thrust. The drag polar represents the aerodynamic behavior of the aircraft, while the fuel consumption is based on the aircraft engine performance characteristics. The drag polar is the relationship between the lift on an aircraft and its drag, expressed in terms of the dependence of the lift coefficient on the drag coefficient. In a first approximation a “parabolic” polar is used, implying that the drag coefficient (Cd) is proportional to the squared lift coefficient (Cl). This first approximation implies the introduction of calculation errors. In a second approximation the compressibility effects are included in order to obtain a realistic drag polar, such that the drag coefficient depends on the lift coefficient and on the Mach number. Further to the fuel consumption, this parameter in a first approach is usually considered as proportional to the engine thrust. In a second approximation, the influence of the actual aircraft speed in the fuel consumption is also considered in order to obtain realistic fuel consumption.

According to some implementations, the whole method is dynamically and continuously performed.

In certain implementations, the method may be carried out by a flight management system of the aircraft.

In yet some implementations of the method, the calculated optimum Mach number may be followed by the aircraft guidance and control system.

According to some implementations of the method, the calculation of the optimum Mach number includes using the following equation:

$C_{v} = {\int_{r_{0}}^{r_{i}}{{C_{f} \cdot \frac{g_{0} \cdot m_{MTOW}}{L_{HV}} \cdot \delta \cdot \frac{C_{CI} + {C_{F}\left\lbrack {M,{C_{T}\left( {M,C_{W}} \right)}} \right\rbrack}}{{M \cdot {\cos\left( {\chi_{TAS} - \chi} \right)}} + {M_{WIND} \cdot {\cos\left( {{\chi_{WIND} - \chi}} \right)}}}\  \cdot d}\; r}}$

wherein C_(v) is the flight costs, C_(f) is a flight fuel costs, g₀ is the standard acceleration of free fall, m_(MTOW) is a maximum takeoff weight, L_(HV) is a fuel lower heating value, δ is an atmospheric pressure ratio, M is a current Mach number of the aircraft, C_(CI) is the cost index coefficient, C_(F) is a fuel consumption parameter, C_(T) is a thrust coefficient, C_(W) is the weight coefficient, |x_(WIND−x)| is the absolute value of the difference between the wind bearing and the aircraft bearing, x_(TAS) is an airspeed yaw angle, x is a ground speed yaw angle, M_(WIND) is a wind Mach number and x_(WIND) is a wind speed yaw angle.

In another implementation, the method includes controlling an aircraft to fly at the optimum economy cruise speed. The method may further include sending the calculated optimum Mach number of the aircraft to the aircraft guidance and control system for adapting the instant speed of the aircraft to the calculated optimum economy cruise speed.

In another implementation, the method for calculating an optimum economy cruise speed in an aircraft is used in ground trajectory predictors and more specifically in ground trajectory predictors that cannot depend on proprietary aircraft performance data. These ground trajectory predictors are generally based on public aircraft performance models.

In yet other embodiments, disclosed are a flight management system, an aircraft including the flight management system, and a computer readable medium having stored therein a computer program that causes a computer to perform the methods of the present disclosure.

According to one embodiment, an aircraft includes an engine that is configured to generate thrust for the aircraft. The aircraft also includes a guidance and control system configured to control a speed of the aircraft by controlling the thrust generated by the engine. Additionally, the aircraft includes a flight management system that includes a computer programmed to receive a plurality of flight parameters including at least a weight of the aircraft, an aircraft bearing and an atmospheric pressure, an atmospheric temperature, a wind speed and a wind bearing at the altitude of the aircraft. The computer is programmed to calculate a cost index coefficient associated with the flight of the aircraft, where the cost index coefficient is based on at least a cost index, the atmospheric pressure, and the atmospheric temperature. The computer is also programmed to calculate a weight coefficient of the aircraft based on at least a weight of the aircraft and the atmospheric pressure at the altitude of the aircraft, calculate a wind Mach number, calculate an absolute value of a difference between the wind bearing and the aircraft bearing, and calculate an optimum Mach number of the aircraft. The optimum Mach number provides the optimum economy cruise speed. The calculation further includes the weight coefficient, the wind Mach number, and the absolute value of the difference between the wind bearing and the aircraft bearing. The guidance and control system is further configured to adapt the speed of the aircraft to the optimum economy cruise speed.

In some implementations of the aircraft, the calculation of the optimum Mach number further includes considering a realistic drag polar that includes compressibility effects and fuel consumption dependencies with aircraft speed and aircraft thrust. In certain implementations of the aircraft, the calculation of the optimum Mach number further includes determining an instantaneous optimum Mach number as a function of the weight coefficient, the wind Mach number, and the absolute value of the bearing difference between the wind and the aircraft path. According to some implementations of the method, the computer of the flight management system dynamically and continuously executes the operations.

In yet another embodiment, a flight management system of an aircraft includes a computer that is programmed to execute operations. The operations include receiving a plurality of flight parameters including at least a weight of the aircraft, an aircraft bearing and an atmospheric pressure, an atmospheric temperature, a wind speed and a wind bearing at the altitude of the aircraft, calculating a cost index coefficient associated with the flight of the aircraft, the cost index coefficient based on at least a cost index, the atmospheric pressure, and the atmospheric temperature, calculating a weight coefficient of the aircraft based on at least a weight of the aircraft and the atmospheric pressure at the altitude of the aircraft, calculating a wind Mach number, calculating an absolute value of a difference between the wind bearing and the aircraft bearing, and calculating an optimum Mach number of the aircraft, which provides the optimum economy cruise speed, wherein the calculation further includes the weight coefficient, the wind Mach number, and the absolute value of the difference between the wind bearing and the aircraft bearing.

In some implementations of the flight management system, the calculation of the optimum Mach number further includes considering a realistic drag polar that includes compressibility effects and fuel consumption dependencies with aircraft speed and aircraft thrust. According to certain implementations of the flight management system, the calculation of the optimum Mach number further comprises determining an instantaneous optimum Mach number as a function of the weight coefficient, the wind Mach number, and the absolute value of the bearing difference between the wind and the aircraft path.

According to some implementations of the flight management system, the computer dynamically and continuously executes the operations.

According to some embodiments, an advantage of at least some of the disclosed embodiments of the present disclosure over solutions disclosed in the state of the art is that the method disclosed herein uses a one step approach to the optimization of the economy cruise speed taking the wind (both along track and crosswind) influence into consideration from the beginning until the end of the flight of the aircraft. The consideration of the crosswind on the optimum Mach number results in a reduction of the flight costs to the minimum. The existing methods or algorithms use a two step approach, wherein the first step optimizes the Mach number in no wind conditions and in the second step a correction due to the wind influence is added. This is intrinsically less efficient than the solution disclosed herein. These existing methods or algorithms provoke FMS implementation issues, problems that are overcome by the one step approach proposed by the present disclosure. An additional advantage of the present disclosure over the solutions disclosed in the state of the art includes, for FMS implementation, the disclosed method provides better results and an intrinsically better approach (directly optimizing considering wind is better than optimizing without considering wind and then correcting for it). As previously described, existing methods and/or algorithms neglect the influence of the crosswind on the optimum speed, and most of them involve other significant simplifications, such as the exclusion of compressibility effects. The present disclosure considers those effects and provides a more precise optimum economy cruise speed.

The methods herein disclosed may be utilized by an Air Traffic Management (ATM) stakeholder involved in analysis or operations requiring applications that rely on trajectory prediction, FMS manufacturers, air navigation service providers (ANSP), ground automation manufacturers and airlines, among others.

The described features, structures, advantages, and/or characteristics of the subject matter of the present disclosure may be combined in any suitable manner in one or more embodiments and/or implementations. In the following description, numerous specific details are provided to impart a thorough understanding of embodiments of the subject matter of the present disclosure. One skilled in the relevant art will recognize that the subject matter of the present disclosure may be practiced without one or more of the specific features, details, components, materials, and/or methods of a particular embodiment or implementation. In other instances, additional features and advantages may be recognized in certain embodiments and/or implementations that may not be present in all embodiments or implementations. Further, in some instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the subject matter of the present disclosure. The features and advantages of the subject matter of the present disclosure will become more fully apparent from the following description and appended claims, or may be learned by the practice of the subject matter as set forth hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the advantages of the subject matter may be more readily understood, a more particular description of the subject matter briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the subject matter and are not therefore to be considered to be limiting of its scope, the subject matter will be described and explained with additional specificity and detail through the use of the drawings, in which:

FIG. 1 is a schematic flow diagram of a particular embodiment of a method of calculating an optimum economy cruise speed of an aircraft; and

FIG. 2 is a schematic flow diagram of a particular embodiment of a method for calculating an optimum economy cruise speed of an aircraft, showing various parameters utilized by the method.

DETAILED DESCRIPTION

Reference throughout this specification to “one embodiment,” “an embodiment,” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Appearances of the phrases “in one embodiment,” “in an embodiment,” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment. Similarly, the use of the term “implementation” means an implementation having a particular feature, structure, or characteristic described in connection with one or more embodiments of the present disclosure, however, absent an express correlation to indicate otherwise, an implementation may be associated with one or more embodiments.

The present disclosure relates to a method for calculating an optimum economy cruise (ECON) speed in an aircraft and the use thereof. The method for calculating an optimum economy cruise speed in an aircraft includes obtaining the Mach number that an aircraft should fly at to minimize the flight costs (e.g., the sum of hourly costs and fuel costs of an aircraft) for a given distance when flying at a given altitude. In some implementations, the method is based on continuously and dynamically monitoring four flight parameters: the weight coefficient (i.e., the weight of the aircraft divided by the atmospheric pressure at the altitude of the aircraft); the cost index coefficient (i.e., the ratio of the cost index of flight of the aircraft divided by the product of the current atmospheric pressure and the square root of the current atmospheric temperature); the wind Mach number (i.e., the current wind speed divided by the speed of sound); and the absolute value of the difference between the wind bearing and the aircraft bearing. The method further includes executing an algorithm that returns the optimum Mach number for the four flight parameters. As the four flight parameters change, the optimum Mach number may be updated accordingly. The present disclosure also provides a method for controlling an aircraft to fly at the previously calculated optimum economy cruise speed.

FIG. 1 shows a schematic flow diagram of a particular embodiment of the method for calculating an optimum economy cruise speed in an aircraft that minimizes flight costs. Firstly, the inputs from a plurality of information providers (onboard sensors and external providers) are received (1) by the FMS, which can be a computer module. The inputs include, at least: the flight distance (distance between departure airport and destination airport), the current fuel load which is measured by the corresponding sensors, the altitude usually provided by the ATC and, the wind conditions provided by a plurality of external sensors such as an anemometer. The cost index, which is calculated as the coefficient between the hourly costs of the aircraft and the fuel costs of the aircraft, can be provided by the airline or the Airline Operations Center (AOC). The atmospheric temperature and pressure are also measured. One or more of these parameters may be continuously updated and received at the FMS. Based on these input parameters, the FMS continuously calculates and monitors (2): the weight coefficient, which is the division of the weight of the aircraft (including fuel weight) by the atmospheric pressure, the cost index coefficient, which is the coefficient between the cost index and the product of the atmospheric pressure by the square root of the atmospheric temperature, the wind Mach number, which is the wind speed divided by the speed of sound, and the absolute value of the difference between the wind bearing and the aircraft bearing.

Then, in some implementations of the method, the FMS calculates the influence of the crosswind (3) along track on the optimum Mach number and the realistic drag polar (4) that includes the compressibility effects, and fuel consumption dependencies with speed and thrust. Once the mentioned parameters have been obtained, the FMS calculates the optimum Economy Cruise (ECON) speed (which, when achieved, minimizes the flight costs), taking said parameters into account, and determines the aircraft Mach number (6).

The optimum economy cruise speed may be sent to the aircraft guidance and control system (7) such that the aircraft may follow the calculated optimum economy cruise speed, or the optimum economy cruise speed may be sent to the ground trajectory predictors (8) in simulation environments.

This method may be dynamically and continuously carried out (9) in order to obtain the actual optimum economy cruise speed of the aircraft in order to minimize the flight costs for the given conditions. For example, the method may be repeated at predetermined intervals to calculate an updated optimum economy cruise speed of the aircraft.

Following, a particular example of an embodiment of the method for calculating an optimum economy cruise speed in an aircraft is disclosed, in a detailed manner.

The following nomenclature has been used throughout the example:

Δ Atmospheric pressure ratio

Γ Air adiabatic index

θ Atmospheric temperature ratio

χ Ground speed yaw angle (aircraft bearing)

χ^(TAS) Airspeed yaw angle (aerodynamic bearing)

χ^(WIND) Wind speed yaw angle (wind bearing)

0 Initial conditions (sub index)

a₀ Standard speed of sound at mean sea level

C_(CI) Cost Index coefficient

C_(D) Drag coefficient

C_(F) Fuel consumption parameter

C_(f) Flight fuel costs

C_(h) Flight hourly costs

CI Cost Index

C_(L) Lift coefficient

C_(T) Thrust coefficient

C_(V) Flight variable costs

C_(W) Weight coefficient

D Drag force

g₀ Standard acceleration of free fall

F Fuel consumption

I Conditions at any point (sub index)

L Lift force

L_(HV) Fuel lower heating value

M Aircraft Mach number

M_(WIND) Wind mach number

m Aircraft mass

m_(MTOW) Maximum Take Off Weight (mass)

P Atmospheric pressure

p₀ Standard pressure at mean sea level

R Aerodynamic pressure coefficient, distance (compressibility coefficient)

S Wing Surface

T Thrust force, atmospheric temperature

t Time

T₀ Standard temperature at mean sea level

v_(G) Ground speed

v_(TAS) True airspeed

v_(WIND) Wind speed

W Weight force

In this particular example, the method uses the following starting relationships to obtain the economy cruise optimum speed:

$\begin{matrix} {{Stationary}\mspace{14mu}{cruise}{\mspace{14mu}\;}{flight}} & \; \\ {L = W} & ({a1}) \\ {T = D} & ({a2}) \\ {{Clean}\mspace{14mu}{aerodynamics}\mspace{14mu}{including}\mspace{14mu}{compressibility}\mspace{14mu}{effects}} & \; \\ {{D/\delta} = {r \cdot M^{2} \cdot C_{D}}} & ({a3}) \\ {{L/\delta} = {r \cdot M^{2} \cdot C_{L}}} & ({a4}) \\ {r = {0.5 \cdot p_{0} \cdot \gamma \cdot S}} & ({a5}) \\ {C_{D} = {f\left( {M,C_{L}} \right)}} & ({a6}) \\ {{Atmospheric}\mspace{14mu}{relationships}} & \; \\ {\delta = {p/p_{0}}} & ({a7}) \\ {\theta = {T/T_{0}}} & ({a8}) \\ {M = \frac{v_{TAS}}{a_{0} \cdot \sqrt{\theta}}} & ({a9}) \\ {M_{WIND} = \frac{v_{WIND}}{a_{0} \cdot \sqrt{\theta}}} & ({a10}) \\ {{Weight}\mspace{14mu}{relationships}} & \; \\ {W = {m \cdot g_{0}}} & ({a11}) \\ {C_{W} = {{m/\delta} \cdot m_{MTOW}}} & ({a12}) \\ {{Thrust}\mspace{14mu}{relationship}} & \; \\ {C_{T} = {\frac{T}{\delta} \cdot \frac{1}{m_{MTOW} \cdot g_{0}}}} & ({a13}) \end{matrix}$

Considering the above cited equations, the thrust coefficient “C_(T)” of the aircraft may be set as a function of the Aircraft Mach number “M” and the weight coefficient “C_(W)”:

$\begin{matrix} {C_{T} = {{\frac{D}{\delta} \cdot \frac{1}{m_{MTOW} \cdot g_{0}}} = \frac{r \cdot M^{2} \cdot {C_{D}\left( {M,C_{L}} \right)}}{m_{MTOW} \cdot g_{0}}}} & ({a14}) \\ {C_{L} = {\frac{1}{r \cdot M^{2}} \cdot \frac{W}{\delta}}} & \left( {a\; 15} \right) \\ {C_{T} = {f\left( {M,C_{W}} \right)}} & \left( {a\; 16} \right) \end{matrix}$

The fuel consumption relationships used include the generic relationship of the fuel consumption coefficient with the Mach number and the thrust coefficient, as well as the cost index relationships as the ratio between hourly and fuel costs:

$\begin{matrix} {C_{F} = {\frac{L_{HV}}{m_{MTOW} \cdot g_{0} \cdot a_{0}} \cdot \frac{F}{\delta\sqrt{\theta}}}} & ({a17}) \\ {C_{F} = {f\left( {M,C_{T}} \right)}} & ({a18}) \\ {{CI} = \frac{C_{h}}{C_{f}}} & ({a19}) \\ {C_{CI} = {\frac{L_{HV}}{m_{MTOW} \cdot g_{0} \cdot a_{0}} \cdot \frac{CI}{\delta\sqrt{\theta}}}} & ({a20}) \end{matrix}$

The ground speed may be defined as the sum of the projection of the airspeed “v_(TAS)” and wind speed “v_(WIND)” over the aircraft path, while the sum of their projections orthogonal to the path shall always be zero: v _(TAS)·sin(χ_(TAS)−χ)+v _(WIND)·sin(χ_(WIND)−χ)=0   (a21) v _(G) =v _(TAS)·cos(χ_(TAS)−χ)+v _(WIND)·cos(χ_(WIND)−χ)   (a22)

Once the ground “v_(G)” speed is obtained, it is introduced in the following algorithm in order to calculate the costs incurred by the aircraft when flying a given distance:

$\begin{matrix} {\mspace{79mu}{C_{v} = {{{\int_{t_{0}}^{t_{i}}{C_{h}d\; t}} - {\int_{m_{0}}^{m_{i}}{C_{f}d\; t}}} = {\int_{r_{o}}^{r_{i}}{{C_{f} \cdot \frac{{CI} + F}{v_{G}} \cdot \ d}\; r}}}}} & ({a23}) \\ {C_{v} = {\int_{r_{0}}^{r_{i}}{{C_{f} \cdot \frac{g_{0} \cdot m_{MTOW}}{L_{HV}} \cdot \delta \cdot \frac{C_{CI} + C_{F}}{{M \cdot {\cos\left( {\chi_{TAS} - \chi} \right)}} + {M_{WIND} \cdot {\cos\left( {\chi_{WIND} - \chi} \right)}}} \cdot \ d}\; r}}} & ({a24}) \\ {C_{v} = {\int_{r_{0}}^{r_{i}}{{C_{f} \cdot \frac{g_{0} \cdot m_{MTOW}}{L_{HV}} \cdot \delta \cdot \frac{C_{CI} + {C_{F}\left\lbrack {M,{C_{T}\left( {M,C_{W}} \right)}} \right\rbrack}}{{M \cdot {\cos\left( {\chi_{TAS} - \chi} \right)}} + {M_{WIND} \cdot {\cos\left( {\chi_{WIND} - \chi} \right)}}} \cdot \ d}\; r}}} & ({a25}) \end{matrix}$

For a constant altitude cruise, in which the atmospheric pressure “δ” is fixed, the above equation can be converted into: Cv=∫ _(r) ₀ ^(r) ^(i) constant·f[C _(W) , M, C _(CI) , M _(WIND), |χWIND−χ|]·dr   (a26)

With the assumption that the wind intensity and its angle with respect to the aircraft path do not depend on the weight coefficient “C_(W)”, this is, they do not vary as the aircraft moves along its trajectory, the variational calculus Euler-Lagrange theorem allows the reduction of the integral problem into a point problem:

$\begin{matrix} {{\frac{\partial f}{\partial M}\left\lbrack {C_{W},{M\left( C_{W} \right)},C_{CI},M_{WIND},{{\chi_{WIND} - \chi}}} \right\rbrack} = \left. 0\rightarrow{M_{OPTIMUM}\left( {C_{W},C_{CI},M_{WIND},{{\chi_{WIND} - \chi}}} \right)} \right.} & ({a27}) \end{matrix}$

The optimum Mach number “M_(OPTIMUM)” that results in the minimum costs is the result of continuously flying the instantaneous Mach number that minimizes the functional “f”. With the drag polar (a6) and the fuel consumption (a18) dependencies taken from the aircraft performance model, the above equation (a27) can be easily solved.

To obtain the minimum costs, the FMS of the aircraft may continuously execute this algorithm, which provides the instantaneous Mach number as a function of the weight coefficient, the cost index coefficient, the wind Mach number and the absolute value of the bearing difference between the wind and the aircraft path.

FIG. 2 shows a schematic block diagram of the most general phases of the particular example of an embodiment of the method for calculating an optimum economy cruise speed in an aircraft. Specifically, the parameters that are dynamically and continuously calculated in the algorithm (10) that is executed by the FMS are: the weight coefficient “C_(W)” (11), the cost index coefficient “C_(CI)” (12), the Wind mach number “M_(WIND)” (13) and the absolute value of the difference between the wind bearing and the aircraft bearing “X−X_(WIND)” (14). As a result of the execution of the algorithm (10) the optimum Aircraft Mach number “M_(OPTIMUM)” is obtained (15).

In this particular example, the weight coefficient is calculated by the FMS as the division of the weight of the aircraft (including the fuel weight) by the atmospheric pressure. Both parameters, the weight of the aircraft and the atmospheric pressure previously, may be continuously and dynamically measured by the measurement system of the aircraft (onboard sensors). Specifically, the initial weight of the aircraft is a known parameter, and the current weight of the aircraft may be calculated by the FMS as the initial weight minus the spent fuel (measured by sensors located in the fuel tanks). The cost index coefficient is calculated starting from a given cost index, and a current atmospheric pressure and current atmospheric temperature. The cost index coefficient may be specifically calculated as the ratio of the cost index divided by the product of the atmospheric pressure and the square root of the atmospheric temperature. In turn, the Wind Mach number is calculated by the FMS as the wind speed divided by the speed of sound, these parameters being previously, continuously and dynamically measured and provided by the measurement system of the aircraft. The absolute value of the difference between the wind bearing and the aircraft bearing is also calculated by the FMS, the wind bearing “χ_(TAS)” and the aircraft bearing “χ” being previously, continuously and dynamically measured by the measurement system of the aircraft.

Embodiments of the methods disclosed may include modeled or simulated parameters as well as measured parameters. For example, in various embodiments, the fuel load of the aircraft may be simulated or estimated based on models of fuel consumption and aircraft performance if measured parameters are unavailable. In ground based simulation environments or due to unavailability of measured parameters, modeled or simulated parameters may be substituted for the measured parameters described herein.

Further, embodiments of the methods disclosed may include a computer programmed to operate in accordance with the methods described herein. The computer may be air-based or land-based. For example, an air-based computer may be associated with an aircraft's flight management system that controls the aircraft on the basis of a calculated optimum economy cruise speed that minimizes flight costs. In another example, a land-based computer system may be located at an air traffic control facility or a mission planning facility for use in ground based trajectory prediction or simulation. The computer may include a processor and a memory for a computer program, that when executed causes the processor to operate in accordance with the methods described herein. The computer program may also be embodied in a computer readable medium having stored therein the computer program.

In the above description, certain terms may be used such as “up,” “down,” “upper,” “lower,” “horizontal,” “vertical,” “left,” “right,” “over,” “under” and the like. These terms are used, where applicable, to provide some clarity of description when dealing with relative relationships. But, these terms are not intended to imply absolute relationships, positions, and/or orientations. For example, with respect to an object, an “upper” surface can become a “lower” surface simply by turning the object over. Nevertheless, it is still the same object. Further, the terms “including,” “comprising,” “having,” and variations thereof mean “including but not limited to” unless expressly specified otherwise. An enumerated listing of items does not imply that any or all of the items are mutually exclusive and/or mutually inclusive, unless expressly specified otherwise. The terms “a,” “an,” and “the” also refer to “one or more” unless expressly specified otherwise. Further, the term “plurality” can be defined as “at least two.”

Additionally, instances in this specification where one element is “coupled” to another element can include direct and indirect coupling. Direct coupling can be defined as one element coupled to and in some contact with another element. Indirect coupling can be defined as coupling between two elements not in direct contact with each other, but having one or more additional elements between the coupled elements. Further, as used herein, securing one element to another element can include direct securing and indirect securing. Additionally, as used herein, “adjacent” does not necessarily denote contact. For example, one element can be adjacent another element without being in contact with that element.

As used herein, the phrase “at least one of”, when used with a list of items, means different combinations of one or more of the listed items may be used and only one of the items in the list may be needed. The item may be a particular object, thing, or category. In other words, “at least one of” means any combination of items or number of items may be used from the list, but not all of the items in the list may be required. For example, “at least one of item A, item B, and item C” may mean item A; item A and item B; item B; item A, item B, and item C; or item B and item C. In some cases, “at least one of item A, item B, and item C” may mean, for example, without limitation, two of item A, one of item B, and ten of item C; four of item B and seven of item C; or some other suitable combination.

Unless otherwise indicated, the terms “first,” “second,” etc. are used herein merely as labels, and are not intended to impose ordinal, positional, or hierarchical requirements on the items to which these terms refer. Moreover, reference to, e.g., a “second” item does not require or preclude the existence of, e.g., a “first” or lower-numbered item, and/or, e.g., a “third” or higher-numbered item.

As used herein, a system, apparatus, structure, article, element, component, or hardware “configured to” perform a specified function is indeed capable of performing the specified function without any alteration, rather than merely having potential to perform the specified function after further modification. In other words, the system, apparatus, structure, article, element, component, or hardware “configured to” perform a specified function is specifically selected, created, implemented, utilized, programmed, and/or designed for the purpose of performing the specified function. As used herein, “configured to” denotes existing characteristics of a system, apparatus, structure, article, element, component, or hardware which enable the system, apparatus, structure, article, element, component, or hardware to perform the specified function without further modification. For purposes of this disclosure, a system, apparatus, structure, article, element, component, or hardware described as being “configured to” perform a particular function may additionally or alternatively be described as being “adapted to” and/or as being “operative to” perform that function.

Some of the functional units described in this specification have been labeled as modules, in order to more particularly emphasize their implementation independence. For example, a module may be implemented as a hardware circuit comprising custom VLSI circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. A module may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like.

Modules may also be implemented in software for execution by various types of processors. An identified module of computer readable program code may, for instance, comprise one or more physical or logical blocks of computer instructions which may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified module need not be physically located together, but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the module and achieve the stated purpose for the module.

Indeed, a module of computer readable program code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within modules, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network. Where a module or portions of a module are implemented in software, the computer readable program code may be stored and/or propagated on in one or more computer readable medium(s).

The computer readable medium may be a tangible computer readable storage medium storing the computer readable program code. The computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing.

More specific examples of the computer readable medium may include but are not limited to a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), an optical storage device, a magnetic storage device, a holographic storage medium, a micromechanical storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, and/or store computer readable program code for use by and/or in connection with an instruction execution system, apparatus, or device.

The computer readable medium may also be a computer readable signal medium. A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electrical, electro-magnetic, magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport computer readable program code for use by or in connection with an instruction execution system, apparatus, or device. Computer readable program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, Radio Frequency (RF), or the like, or any suitable combination of the foregoing.

In one embodiment, the computer readable medium may comprise a combination of one or more computer readable storage mediums and one or more computer readable signal mediums. For example, computer readable program code may be both propagated as an electro-magnetic signal through a fiber optic cable for execution by a processor and stored on RAM storage device for execution by the processor.

Computer readable program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

The schematic flow chart diagrams included herein are generally set forth as logical flow chart diagrams. As such, the depicted order and labeled steps are indicative of one embodiment of the presented method. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more steps, or portions thereof, of the illustrated method. Additionally, the format and symbols employed are provided to explain the logical steps of the method and are understood not to limit the scope of the method. Although various arrow types and line types may be employed in the flow chart diagrams, they are understood not to limit the scope of the corresponding method. Indeed, some arrows or other connectors may be used to indicate only the logical flow of the method. For instance, an arrow may indicate a waiting or monitoring period of unspecified duration between enumerated steps of the depicted method. Additionally, the order in which a particular method occurs may or may not strictly adhere to the order of the corresponding steps shown.

The present subject matter may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope. 

What is claimed is:
 1. A method for calculating an optimum economy cruise speed of an aircraft, the method comprising: receiving a plurality of flight parameters including at least a weight of the aircraft, an aircraft bearing, an atmospheric pressure, an atmospheric temperature, a wind speed, and a wind bearing at a flight altitude of the aircraft; calculating a cost index coefficient associated with a flight of the aircraft, the cost index coefficient based on at least a cost index, the atmospheric pressure, and the atmospheric temperature; calculating a weight coefficient of the aircraft based on at least the weight of the aircraft and the atmospheric pressure at the flight altitude of the aircraft; calculating a wind Mach number; calculating an absolute value of a difference between the wind bearing and the aircraft bearing; and calculating an optimum Mach number of the aircraft, which provides the optimum economy cruise speed, wherein the calculation of the optimum Mach number comprises the weight coefficient, the cost index coefficient, the wind Mach number and the absolute value of the difference between the wind bearing and the aircraft bearing; and sending the optimum Mach number of the aircraft to an aircraft guidance and control system and controlling an instant speed of the aircraft to the optimum economy cruise speed.
 2. The method according to claim 1, wherein a fuel load of the aircraft is dynamically and continuously measured to calculate the weight of the aircraft.
 3. The method according to claim 1, wherein the atmospheric pressure at the altitude of the aircraft is dynamically and continuously measured to calculate the altitude of the aircraft.
 4. The method according to claim 1, wherein the calculation of the optimum Mach number further comprises considering a realistic drag polar that includes compressibility effects and fuel consumption dependencies with aircraft speed and aircraft thrust.
 5. The method according to claim 4, wherein the calculation of the optimum Mach number further comprises determining an instantaneous optimum Mach number as a function of the weight coefficient, the cost index coefficient, the wind Mach number and the absolute value of the bearing difference between the wind and the aircraft path.
 6. The method according to claim 1, wherein the method is dynamically and continuously carried out.
 7. The method according to claim 1, wherein the cost index comprises a fixed cost index relating a fuel cost of the aircraft and an hourly cost of the aircraft.
 8. The method according to claim 1, wherein the cost index coefficient is calculated as the ratio of the cost index divided by the product of the atmospheric pressure and the square root of the atmospheric temperature.
 9. The method according to claim 8, wherein calculating the weight coefficient comprises division of the weight of the aircraft by the atmospheric pressure at the altitude of the aircraft.
 10. The method according to claim 9, wherein calculating the wind Mach number comprises division of the wind speed by the speed of sound.
 11. The method according to claim 1, further comprising sending the optimum Mach number of the aircraft as calculated to a ground trajectory predictor, wherein the ground trajectory predictor is configured to predict a trajectory of the aircraft at the optimum Mach number.
 12. An aircraft, comprising: an engine, configured to generate thrust for the aircraft; a guidance and control system configured to control a speed of the aircraft by controlling the thrust generated by the engine; and a flight management system comprising a computer programmed to execute the operations of: receiving a plurality of flight parameters including at least a weight of the aircraft, an aircraft bearing, an atmospheric pressure, an atmospheric temperature, a wind speed, and a wind bearing at an altitude of the aircraft; calculating a cost index coefficient associated with a flight of the aircraft, the cost index coefficient based on at least a cost index, the atmospheric pressure, and the atmospheric temperature; calculating a weight coefficient of the aircraft based on at least a weight of the aircraft and the atmospheric pressure at the altitude of the aircraft; calculating a wind Mach number; calculating an absolute value of a difference between the wind bearing and the aircraft bearing; and calculating an optimum Mach number of the aircraft, which provides an optimum economy range cruise speed, wherein the calculation of the optimum Mach number comprises the weight coefficient, the cost index coefficient, the wind Mach number, and the absolute value of the difference between the wind bearing and the aircraft bearing; wherein the guidance and control system controls the speed of the aircraft to the optimum economy cruise speed.
 13. The aircraft according to claim 12, wherein the calculation of the optimum Mach number further comprises considering a realistic drag polar that includes compressibility effects and fuel consumption dependencies with aircraft speed and aircraft thrust.
 14. The aircraft according to claim 13, wherein the calculation of the optimum Mach number further comprises determining an instantaneous optimum Mach number as a function of the weight coefficient, the wind Mach number, and the absolute value of the bearing difference between the wind and the aircraft path.
 15. The aircraft according to claim 12, wherein the computer of the flight management system dynamically and continuously executes the operations.
 16. A flight management system of an aircraft, comprising a computer programmed to execute the operations of: receiving a plurality of flight parameters including at least a weight of the aircraft, an aircraft bearing, an atmospheric pressure, an atmospheric temperature, a wind speed, and a wind bearing at the altitude of the aircraft; calculating a cost index coefficient associated with a flight of the aircraft, the cost index coefficient based on at least a cost index, the atmospheric pressure, and the atmospheric temperature; calculating a weight coefficient of the aircraft based on at least a weight of the aircraft and the atmospheric pressure at the altitude of the aircraft; calculating a wind Mach number; calculating an absolute value of a difference between the wind bearing and the aircraft bearing; and calculating an optimum Mach number of the aircraft, which provides an optimum economy cruise speed, wherein the calculation of the optimum Mach number comprises the weight coefficient, the cost index coefficient, the wind Mach number, and the absolute value of the difference between the wind bearing and the aircraft bearing; wherein the flight management system further comprises a guidance and control system controlling an instant speed of the aircraft to the optimum economy cruise speed in response to the optimum Mach number of the aircraft.
 17. The flight management system according to claim 16, wherein the calculation of the optimum Mach number further comprises considering a realistic drag polar that includes compressibility effects and fuel consumption dependencies with aircraft speed and aircraft thrust.
 18. The flight management system according to claim 17, wherein the calculation of the optimum Mach number further comprises determining an instantaneous optimum Mach number as a function of the weight coefficient, the wind Mach number, and the absolute value of the bearing difference between the wind and the aircraft path.
 19. The flight management system according to claim 16, wherein the computer dynamically and continuously executes the operations. 